Effective Generation of Dynamically Balanced Locomotion with Multiple Non-coplanar Contacts

Studies of computationally and analytically convenient approximations of rigid body dynamics have brought valuable insight into the field of humanoid robotics. Additionally, they facilitate the design of effective walking pattern generators. Going further than the classical Zero Moment Point-based methods, this paper presents two simple and novel approaches to solve for 3D locomotion with multiple non-coplanar contacts. Both formulations use model predictive control to generate dynamically balanced trajectories with no restrictions on the center of mass height trajectory. The first formulation treats the balance criterion as an objective function, and solves the control problem using a sequence of alternating convex quadratic programs. The second formulation considers the criterion as constraints, and solves a succession of convex quadratically constrained quadratic programs.

[1]  J. Trinkle,et al.  On Dynamic Multi‐Rigid‐Body Contact Problems with Coulomb Friction , 1995 .

[2]  Andrei Herdt,et al.  LMPC based online generation of more efficient walking motions , 2012, 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012).

[3]  Shuuji Kajita,et al.  Dynamics and balance of a humanoid robot during manipulation tasks , 2006, IEEE Transactions on Robotics.

[4]  Yutaka Uchimura,et al.  3DZMP-based control of a humanoid robot with reaction forces at 3-dimensional contact points , 2010, 2010 11th IEEE International Workshop on Advanced Motion Control (AMC).

[5]  Eiichi Yoshida,et al.  RobOptim: an Optimization Framework for Robotics , 2013 .

[6]  Shuuji Kajita,et al.  International Journal of Humanoid Robotics c ○ World Scientific Publishing Company An Analytical Method on Real-time Gait Planning for a Humanoid Robot , 2022 .

[7]  Pierre-Brice Wieber,et al.  Trajectory Free Linear Model Predictive Control for Stable Walking in the Presence of Strong Perturbations , 2006, 2006 6th IEEE-RAS International Conference on Humanoid Robots.

[8]  Ambarish Goswami,et al.  Postural Stability of Biped Robots and the Foot-Rotation Indicator (FRI) Point , 1999, Int. J. Robotics Res..

[9]  Miomir Vukobratovic,et al.  Zero-Moment Point - Thirty Five Years of its Life , 2004, Int. J. Humanoid Robotics.

[10]  Pierre-Brice Wieber,et al.  Viability and predictive control for safe locomotion , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[11]  Russ Tedrake,et al.  A direct method for trajectory optimization of rigid bodies through contact , 2014, Int. J. Robotics Res..

[12]  Shuuji Kajita,et al.  A universal stability criterion of the foot contact of legged robots - adios ZMP , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[13]  Andrei Herdt,et al.  Walking without thinking about it , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[14]  Lorenz T. Biegler,et al.  On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming , 2006, Math. Program..

[15]  Kazuhito Yokoi,et al.  The 3D linear inverted pendulum mode: a simple modeling for a biped walking pattern generation , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[16]  Sung-Hee Lee,et al.  Reaction Mass Pendulum (RMP): An explicit model for centroidal angular momentum of humanoid robots , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[17]  Nikos D. Sidiropoulos,et al.  Feasible Point Pursuit and Successive Approximation of Non-Convex QCQPs , 2014, IEEE Signal Processing Letters.

[18]  Roy Featherstone,et al.  Rigid Body Dynamics Algorithms , 2007 .

[19]  Amir Ali Ahmadi,et al.  Control design along trajectories with sums of squares programming , 2012, 2013 IEEE International Conference on Robotics and Automation.